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对于V-BLAST系统的检测,最大似然(ML)算法有着最优的性能却也有最大的计算复杂度;经典的排序连续干扰抵消(OSIC)算法复杂度较低,但数值稳定性差,且性能与ML差距较大。因此,本文基于检测性能和计算复杂度折中的思想,针对4×4 V-BLAST系统提出了一种分组最大似然(Group ML,GML)检测算法,在保证较好检测性能的基础上,通过将四维ML检测器分成两组二维ML检测器来降低计算复杂度。此外,本文还提出了一种简化的最大似然(Simpli-fied ML,SML)检测算法,通过将每组中的二维ML检测器的搜索空间从二维降至一维,进一步降低了计算复杂度,并证明其与ML算法具有一致的性能。仿真表明,在误符号率为10-3时GML算法相比OSIC算法有约7dB的性能提升。经分析知,GML算法复杂度与ML-OSIC算法相比在高阶调制方式下有着显著的降低,易于硬件实现。
The maximum likelihood (ML) algorithm has the best performance and the largest computational complexity for V-BLAST system detection. The classical sequential sequential interference cancellation (OSIC) algorithm has low complexity but poor numerical stability, and the performance With the larger gap between ML. Therefore, based on the compromise between detection performance and computational complexity, this paper proposes a group ML (GML) detection algorithm for 4 × 4 V-BLAST system. On the basis of ensuring good detection performance, The computational complexity is reduced by splitting the four-dimensional ML detector into two sets of two-dimensional ML detectors. In addition, this paper also presents a simplified algorithm of Simpli-fied ML (SML) detection, which further reduces the computation by reducing the search space of two-dimensional ML detector in each group from two-dimensional to one-dimensional Complexity, and prove it has the same performance with ML algorithm. The simulation results show that the GML algorithm has about 7dB performance improvement compared with the OSIC algorithm when the symbol error rate is 10-3. The analysis shows that, compared with the ML-OSIC algorithm, the complexity of the GML algorithm has a significant reduction in high-order modulation mode, easy to implement in hardware.